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Record W4399712588 · doi:10.3208/jgssp.v10.p1-01

Characterisation of the behaviour of liquefaction triggering in a cyclic undrained simple shear test setting

2024· article· en· W4399712588 on OpenAlexaboutno aff
Hugo Portugal, C. Sigarán-Loría, Ronald Brinkgreve

Bibliographic record

VenueJapanese Geotechnical Society Special Publication · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersTechnische Universiteit Delft
KeywordsGeotechnical engineeringLiquefactionSimple shearGeologyShear (geology)Direct shear testSimple (philosophy)Test (biology)Petrology

Abstract

fetched live from OpenAlex

The definition of appropriate calibration criteria for liquefaction-simulating constitutive models in sands is essential to properly simulate a liquefied state under seismic ground motions, enabling an adequate estimation of the liquefaction hazard. Therefore, a thorough quantitative characterisation of the behaviour of liquefaction is necessary to define liquefaction-triggering criteria that can describe a liquefied state in terms of stress and deformation. This paper presents a benchmark characterisation study of the behaviour of liquefaction, where liquefaction-triggering criteria, in terms of pore pressure ratio (ru) and shear strain (γ), were determined using two cyclic undrained direct simple shear test databases of Ottawa F-65 sand. The behaviour of liquefaction was analysed considering variations of initial state, confinement pressure (σ’v0) and cyclic shearing (CSR) conditions. The onset of liquefaction-triggering markers was evaluated in terms of moment of occurrence. The research concluded that liquefaction-triggering markers ru = 0.95 and γ = 3% could be used simultaneously to indicate the initiation of liquefaction in loose and dense Ottawa F-65 sand under various initial and cyclic shearing conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.215
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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